How to Install & Run TensorRT on RunPod, Unix, Linux for 2x Faster Stable Diffusion Inference Speed

Stable Diffusion Gets A Major Boost With RTX Acceleration. One of the most common ways to use Stable Diffusion, the popular Generative AI tool that allows users to produce images from simple text descriptions, is through the Stable Diffusion Web UI by Automatic1111. In today’s Game Ready Driver, NVIDIA added TensorRT acceleration for Stable Diffusion Web UI, which boosts GeForce RTX performance by up to 2X. In this tutorial video I will show you everything about this new Speed up via extension installation and TensorRT SD UNET generation on RunPod. The tutorial can be also used on other Unix systems and on local Linux Operating Systems.

TensorRT #StableDiffusion #NVIDIA

Automatic Installer Of Tutorial ⤵️
https://www.patreon.com/posts/86438018

Comprehensive TensorRT Main Tutorial ⤵️
https://youtu.be/kvxX6NrPtEk

TensorRT Official GitHub Repo ⤵️
https://github.com/NVIDIA/Stable-Diffusion-WebUI-TensorRT

0:00 Introduction to speed increase of TensorRT — RTX Acceleration on RunPod & Unix
3:10 Image quality comparison of TensorRT on vs TensorRT off for Stable Diffusion XL (SDXL)
4:14 How to install TensorRT on RunPod and on local Unix operating systems
7:30 How to check your current Nvidia driver on RunPod and on Unix
8:10 Extra tips for TensorRT
8.45 How to connect / open your Automatic1111 Web UI on RunPod
9:27 How to enable quick selection drop down options for VAE and TensorRT UNET
10:09 How to generate your first TensorRT model
10:19 TensorRT engine generation speed and duration
10:55 How to reload last image generation settings quickly
11:44 The amount of speed increase on RTX 3090 on RunPod with TensorRT